Introduction: C3 glomerulopathy (C3G) is a rare, progressive kidney disease resulting from dysregulation of the alternative pathway (AP) of complement. Biomarkers at baseline were investigated in patients with C3G who participated in two phase 2 studies with the factor D (FD) inhibitor, danicopan. Methods: Patients with biopsy-confirmed C3G, proteinuria ≥500 mg/day, and estimated glomerular filtration rate (eGFR) ≥30 mL/min/1.73 m2 were enrolled into two studies (NCT03369236 and NCT03459443). Biomarker analysis was performed for patients with C3G confirmed by central pathology laboratory re-evaluation. Complement and clinical biomarkers, biopsy composite score, and activity and chronicity indices were assessed at baseline and analyzed by pairwise Spearman correlation analysis. Results: Twenty-nine patients were included in the analysis (median [interquartile range] age: 24.0 [10.0] years). Systemic complement AP activation was evident by reduced median concentrations of C3 and C5, elevated sC5b-9, and normal C4, relative to reference ranges. C3 showed strong pairwise correlations with C5 and sC5b-9 (r = 0.80 and −0.73, respectively; p < 0.0001). Baseline Ba and FD concentrations were inversely correlated with eGFR (r = −0.83 and −0.87, respectively; p < 0.0001). Urinary concentrations of sC5b-9 were correlated with both plasma sC5b-9 and proteinuria (r = 0.69 and r = 0.83, respectively; p < 0.0001). Biopsy activity indices correlated strongly with biomarkers of systemic AP activation, including C3 (r = −0.76, p < 0.0001), whereas chronicity indices aligned more closely with eGFR (r = −0.57, p = 0.0021). Conclusion: Associations among complement biomarkers, kidney function, and kidney histology may add to the current understanding of C3G and assist with the characterization of patients with this heterogenous disease.

© 2022 The Author(s). Published by S. Karger AG, Basel

Introduction

C3 glomerulopathy (C3G) is a rare, chronic, progressive glomerulopathy associated with dysregulation of the alternative pathway (AP) of complement and characterized by the dominant deposition of AP proteins, particularly C3 fragments, within glomeruli [1-4]; kidney biopsy is required for a definitive diagnosis of C3G [1]. There are currently no approved treatments for C3G and up to 50% of patients reach end-stage kidney disease within 10 years of diagnosis [2, 4-9].

In most patients with C3G, dysregulation of the AP is observed in the fluid phase and on activating surfaces within the glomerular microenvironment with variable activation of the terminal complement pathway [4]. This dysregulation is indicated by excessive consumption of C3 and the deposition of C3 fragments in the kidney; an essential step for AP activation is factor D (FD) cleavage of factor B (FB) to form C3 convertase (see Fig. 1). AP dysregulation may be driven by pathogenic variants in the genes encoding complement proteins and/or by autoantibodies, such as nephritic factors (e.g., C3 nephritic factor [C3NeF] and C5 nephritic factor [C5NeF]) that stabilize the C3 and C5 convertases, respectively. C3G can be heterogenous in terms of clinical presentation, outcomes, and even potentially in terms of biomarker profiles, with fluctuating nephritic factor activity, multiple autoantibodies, and the presence of multiple complement gene variants; however, not all patients with C3G have identified pathogenic variants or autoantibodies in the AP [4, 7, 10]. Therefore, full profiling of patient characteristics, including noninvasive biomarkers, may prove useful in assessing complement dysregulation.

Fig. 1.

Complement pathways including biomarkers relevant to C3G. Simplified schematic of the complement pathways with the focus on the C3 and C5 convertase complexes of the AP and the terminal pathway. Once activated, the classical and lectin pathways lead to the formation of C4b2a, a C3 convertase. The AP is continuously activated in plasma by low-grade spontaneous hydrolysis of C3. FB in complex with activated C3 is cleaved by FD, an essential step, to form the C3 convertase C3bBb, which then cleaves C3 to C3a and C3b. This activation is amplified by the covalent binding of a small amount of C3b to hydroxyl groups on cell-surface carbohydrates and proteins of target cells. This cell-surface C3b binds FB which is cleaved by FD to Ba and Bb; Bb remains associated with C3b to form more C3bBb, which creates the amplification loop. Ba is the free fragment of FB that results from the activation of the AP. Accumulated C3b also binds C3 convertase, forming the C5 convertase (C3bBbC3b), which cleaves the C5 complement protein to C5a and C5b. Surface-bound C5b leads to the terminal pathway and the formation of soluble(s) C5b-9 or the membrane attack complex (C5b-9). The AP is regulated by soluble and bound regulatory proteins to prevent nonspecific damage to host cells and to limit the deposition of complement to the surface of pathogens. However, autoantibodies that stabilize C3 and C5 convertases (C3NeF and C5NeF, respectively) and inhibit the complement regulator factor H (FH, not shown), and genetic variants in key complement regulators such as FH, cause dysregulation of the AP of complement. Activation of the AP leads to consumption of C3, the induction of an inflammatory response through soluble C3a and C5a fragments and deposition of C3 fragments in the GBM of the kidney, which subsequently promotes cell clearance, drives the amplification loop, and enables terminal complement activation causing cell lysis and sublytic effects. AP, alternative pathway; FB, factor B; FD, factor D; C3NeF, nephritic factor C3; C5NeF, nephritic factor C5; GBM, glomerular basement membrane.

In many patients with C3G, differing levels of complement components in serum and plasma may provide insight into AP dysregulation, potentially also suggesting variable importance of complement disruption at different stages of disease, or in different patient subpopulations [7, 11, 12]. Further analyses of biomarker profiles and pathogenetic mechanisms may assist with defining patients and, as multiple complement-directed therapies become available, personalized therapeutic approaches [13]. The present analysis examines baseline blood and urine biomarker distributions, kidney function parameters, and biopsy scores of C3G patients enrolled in two clinical studies of danicopan (ALXN2040), an oral small-molecule inhibitor of the FD serine protease that is essential for AP activation.

Materials and MethodsStudy Design

This investigation utilized baseline (prior to investigational drug dosing) data from patients enrolled in two phase 2 studies that investigated the safety and efficacy of the FD inhibitor danicopan. Study 204 (NCT03369236) was a double-blind, placebo-controlled, randomized, 6-month (plus open-label extension) trial of patients with biopsy-confirmed C3G treated with danicopan or placebo [14]. Study 205 (NCT03459443) was a single-arm, open-label, 12-month (plus extension) trial of patients with biopsy-confirmed C3G or immune complex membranoproliferative glomerulonephritis treated with danicopan [15]. Further details of the full methodology and outcomes of these two studies are described in a separate article (Nester et al., manuscript submitted). The current biomarker analyses included: (1) evaluation of complement biomarkers at baseline in blood (serum or plasma) and urine; (2) evaluation of genetic variants and acquired factors (C3NeF) as potential disease drivers; (3) histopathologic scoring of disease activity and chronicity; and (4) exploration of pairwise relationships (Spearman correlations) between complement biomarkers, clinical measures of kidney function (estimated glomerular filtration rate [eGFR] and proteinuria), and kidney biopsy scores.

Patients

Key eligibility criteria for the two studies are shown in online Supplementary Table 1 (for all online suppl. material, see www.karger.com/doi/10.1159/000527166). Patients were excluded if they had an eGFR <30 mL/min/1.73 m2 as calculated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation (2009) for patients ≥19 years and the “Bedside Schwartz” equation (2009) for patients <19 years [16, 17].

For enrollment in the two studies, all patients were required to have a local diagnosis of C3G (204 and 205 studies) or immune complex membranoproliferative glomerulonephritis (205 study) by biopsy. Kidney biopsies were performed during screening (pretreatment) according to local practices to obtain a baseline histology score. Alternatively, a historical local biopsy (collected within approximately 6 months of the start of study treatment) was permitted provided it met the analysis requirements. Biopsies were subsequently evaluated at a central pathology laboratory (Centre for Inflammatory Disease, Imperial College London, London, UK) by light microscopy, immunofluorescence, and electron microscopy. Confirmation of C3G included the presence of C3 deposits of ≥2 orders of intensity greater than any other immune reactant (IgG, IgA, IgM, and C1q) [18]. Glomerular histology was evaluated using a biopsy scoring system: chronicity indices (scale 0–12) represented the presence of glomerular sclerosis, fibrous crescents, tubular atrophy, and interstitial fibrosis; activity indices (scale 0–15) represented the presence of endocapillary and mesangial hypercellularity, capillary neutrophils, cellular crescents, and necrosis; and a biopsy composite score (scale 0–21) incorporated activity indices plus scores for C3 intensity and degree of macrophage infiltration (each scale 0–3) (online Suppl. Information S1). Classification of C3G into its two subclasses C3 glomerulonephritis (C3GN) and dense deposit disease (DDD) was based on electron microscopy [18, 19]; DDD was diagnosed by the presence of highly electron-dense intramembranous deposits, and C3GN was diagnosed as C3G lacking these deposits. Only patients with a C3G diagnosis confirmed by a central pathology laboratory (“central pathologist confirmed”) were included in the current biomarker analysis.

Analysis of Biomarkers of Complement System ActivitySampling

Whole blood samples, first morning urine, and 24-h urine samples (at least 7 days post-screening biopsy) were taken during screening (24-h urine) or just prior to dosing. Whole blood was processed to obtain serum or plasma, and urine was cleared by centrifugation; samples were stored at −80°C until analyzed.

Analysis

Urine was assayed for total protein, creatinine concentrations, and total protein:creatinine ratio. Serum AP activity was evaluated using the AP Wieslab functional ELISA (SVAR, Sweden) and serum classic pathway (CP) activity by complement activation enzyme immunoassay (CAE, DiaSorin, Italy). Serum C3 and C4 concentrations were determined by immunoturbidimetric assay (Tina-quant) for Cobas analyzer (Roche Diagnostics, Switzerland). Commercial ELISA kits were used to determine concentrations of the complement components serum FD (Quantikine, R&D Systems, USA); plasma Ba, Bb, and sC5b-9 (MicroVue, Quidel, USA); and plasma C5 (Human C5 ELISA, Abcam, UK). Urine Ba and sC5b-9 were assayed by ELISA at varying dilutions (Quantikine, Quidel, USA) and normalized to creatinine; urine sC5b-9 values below the lower limit of quantitation were set to lower limit of quantitation prior to normalization for all analyses.

Analyses were performed by central clinical laboratories for the AP Wieslab and CP functional assays, serum FD, and plasma Ba, Bb, and sC5b-9; by local clinical laboratories for serum C3 and C4 and urinary protein and creatinine; and by a non-GLP research laboratory for plasma C5 and urinary Ba and sC5b-9.

Genetic and Autoantibody Analysis

Targeted sequencing and duplication/deletion detection were performed on DNA extracted from whole blood samples to identify variants in genes implicated in C3G pathogenesis including complement and complement regulatory genes. The presence of C3NeF was evaluated in a functional C3 convertase stabilization assay and a confirmatory binding assay, and anti-factor H autoantibody was identified using a custom ELISA assay (online Suppl. Information S2).

Data Interpretation and Analysis

Patient demographics, clinical and biomarker characteristics were summarized descriptively (median, interquartile range [IQR], and percentage of patients). For biomarkers, the lower and upper limits of normality (LLN and ULN) were determined by clinical laboratories, in-house, or by the assay manufacturer (online Suppl. Table 2).

Pairwise nonparametric Spearman correlation coefficients (rs) and two-tailed p values were determined systematically for biomarkers of kidney function (eGFR and proteinuria), complement status (serum, plasma, and urine), and histopathology (biopsy scores) using Prism software (version 8; GraphPad Software, San Diego, USA). A correlogram, depicting significant pairwise correlations (p < 0.05), was prepared using RStudio software with corrplot package (R version 4.1.1 [2021-08-10]; https://www.R-project.org/). Due to the nature of C3 and C5b-9 deposition data collection, assessment of any correlations between AP biomarker levels and deposit intensities was not possible in this study.

ResultsBaseline Characteristics

Twenty-nine of the 35 enrolled patients in both phase 2 trials had central pathologist-confirmed C3G. Of these, 22 were diagnosed with C3GN and 7 with DDD (online Suppl. Fig. 1). Patients had a median (IQR) age of 24.0 (10.0) years, a duration of disease of 5.5 (5.8) years, and eGFR of 81.2 (66.3) mL/min/1.732 (Table 1). The medians (IQRs) for biopsy composite score, activity index, and chronicity index were 11.0 (5.0, on a scale 0–21), 6.0 (5.0, on a scale 0–15), and 5.0 (5.0, on a scale 0–12), respectively, with a higher value indicating greater severity or higher incidence of glomerular findings (online Suppl. Table 3). Most patients had a history of treatment with angiotensin-converting enzyme inhibitors/receptor blockers (27/29 [93.1%]) and/or immunosuppressant therapy (21/29 [72.4%]) and 4 (13.8%) had previously received eculizumab (online Suppl. Table 4).

Table 1.

Patient demographics and disease characteristics

Genetic and Autoantibody Analysis

Twenty-seven patients consented to genetic analysis; 12 rare or unique, nonsynonymous, heterozygous genomic variants were classified. No variants were classified as pathogenic or likely pathogenic. Nine patients (31.0%) had C3NeF antibody and 4 (13.8%) were positive for anti-factor H antibody (Table 1). However, six variants in 6 patients were characterized as variants of uncertain significance (6/27; 22.2%). An additional six variants in 5 patients were characterized as benign. In total, the 12 variants were distributed across six genes (C3, CD46, CFB, CFH, CFHR5, and THBD); 11 of the 12 were missense variants, three of which were considered novel variants not previously reported (one in C3 and two in THBD) (online Suppl. Table 5).

Baseline Biomarkers

Compared with reference ranges for healthy individuals, the median values of C3 and C5 concentrations were lower than the LLN (2.33 µmol/L vs. LLN 4.33–5.0 µmol/L and 40.0 µg/mL vs. LLN 50 µg/mL, for C3 and C5, respectively), whereas median values of sC5b-9 and Bb were higher than the ULN (597 µg/L vs. ULN 467 µg/L and 1.79 mg/L vs. 1.42 mg/L, for sC5b-9 and Bb, respectively). As a comparison, the median concentrations of C4, a biomarker specific for CP and lectin pathway, were within the normal range. Notably, 79.3% and 58.6% of patients had C3 and C5 concentrations, respectively, below their respective LLNs, whereas 65.5% and 72.4% of patients had sC5b-9 and Bb concentrations, respectively, above their respective ULNs. Additionally, the concentration values of FD and Ba were greater than the ULN in a substantial minority of patients (44.8% and 37.9% of patients for FD and Ba, respectively; Fig. 2 and see online Suppl. Table 2 for data on additional biomarkers including AP and CP activity).

Fig. 2.

Concentrations of baseline circulating complement biomarkers in plasma/serum. Solid and dotted black lines show medians and quartiles, respectively. Gray hashed lines and shading represent the normal biomarker ranges (ULN and LLN); for C3 and C4, the gray lines represent the highest of multiple ULN values and the lowest of multiple LLN values (see online Suppl. Table 2 for these ranges). LLN, lower limit of normal; ULN, upper limit of normal.

Correlation Analysis

A systematic pairwise correlation analysis was undertaken including systemic and urinary complement biomarkers, disease characteristics (disease duration), kidney function (proteinuria and eGFR), and biopsy scores. The complete matrix of statistically significant (p < 0.05) Spearman correlations is depicted in a correlogram (Fig. 3) with selected correlations shown graphically (Fig. 4).

Fig. 3.

Correlogram of associations across complement biomarkers, disease duration, kidney function, and kidney pathology. Spearman correlogram showing significant pairwise correlations (p < 0.05) among duration of disease (n = 28), systemic (plasma/serum) and urinary complement proteins (n = 29), and kidney biopsy scores for activity, chronicity, and a composite score (n = 27; see online supplementary information S1 for biopsy scoring system) (full dataset N = 29). Red hues represent negative correlations; blue hues represent positive correlations. The color intensity and circle sizes represent r coefficient values. Green boxes indicate clusters of cross-correlated biomarkers as described in the results. APW, AP Wieslab (alternative pathway activity); CP, classical pathway activity; Cr, creatinine; eGFR, estimated glomerular filtration rate; FD, factor D; PCR, protein creatinine ratio.

Fig. 4.

Correlations of serum concentrations of C3 with (ai) C5 and (aii) sC5b-9 in plasma, for urinary concentrations of sC5b-9 with (aiii) sC5b-9 in plasma and (iv) proteinuria, and for kidney function, represented by eGFR, with the systemic biomarkers (bi) Ba and (bii) FD. Gray areas represent the normal ranges for the systemic biomarkers C3 and C5 (ai), C3 and sC5b-9 (aii), sC5b-9 only (aiii), Ba only (bi), and FD only (bii); urine biomarkers are low or undetectable in healthy individuals and, therefore, normal ranges are not shown (urine sC5b-9/creatinine in aiii and aiv and protein/creatinine in iv). R values determined by Spearman correlation analysis. Trend lines shown for illustrative purposes only.

Systemic Biomarkers of Complement Activity

The largest grouping of strong pairwise correlations was observed among the systemic complement biomarkers. Complement C3, for example, showed strong positive correlation with C5 (r = 0.80; p < 0.0001) and a strong negative correlation with sC5b-9 (r = −0.73; p < 0.0001), indicating a concerted dysregulation from AP through the terminal pathway (Fig. 3, 4). Additionally, ex vivo measurements of AP and CP activity were diminished or eliminated in serum from patients with strong dysregulation, evidenced by strong positive correlations with C3 (r = 0.95 and 0.86, respectively; p < 0.0001) and strong negative correlations with sC5b-9 (r = −0.72 and −0.83, respectively; p < 0.0001) (Fig. 3).

Although Bb is a direct cleavage product of the AP protein FB, plasma Bb levels were not strongly correlated with C3 or the other markers of systemic dysregulation. Its strongest association was a moderate, positive correlation with the fellow FB cleavage product plasma Ba (r = 0.52, p = 0.0041); Bb elevation was otherwise somewhat decoupled from the dysregulation seen in central and terminal complement biomarkers (Fig. 3).

Biomarkers of Complement Activity and Kidney Function (eGFR)

Although eGFR showed no significant correlations with the systemic biomarkers C3, C5, and sC5b-9, assessments revealed strong inverse correlations of eGFR with plasma Ba and serum FD levels (r = −0.83 and r = −0.87, respectively; p < 0.0001) (Fig. 3). The correlations were sufficiently strong that Ba and FD were both within normal range in all patients with eGFR >90 mL/min/1.73 m2 yet elevated in most patients with eGFR below 60 mL/min/1.73 m2 (Fig. 4).

Urine Biomarkers of Complement Activity

Assessment of urinary complement biomarkers normalized to creatinine highlighted that urinary sC5b-9 and urinary Ba were detected over a wide range of concentrations and were influenced both by their plasma concentrations and by proteinuria, as indicated by moderate to strong correlations: r = 0.69 and 0.83 for urinary sC5b-9 versus plasma sC5b-9 and proteinuria, respectively (p < 0.0001; Fig. 4), and r = 0.52 and 0.74 for urinary Ba versus plasma Ba and proteinuria (p = 0.0036 and p < 0.0001, respectively). The two urine complement proteins therefore were more strongly correlated with proteinuria than with their plasma counterparts.

Biomarkers of Complement Activity and Kidney Pathology

Biopsy composite scores correlated with markers of systemic AP activation include C3 (r = −0.70; p = 0.0000), C5 (r = −0.53; p = 0.0046), and sC5b-9 (r = 0.64; p = 0.0003), as did biopsy activity indices (r = −0.76, −0.58 and 0.67; p < 0.0001, p = 0.0017, and p = 0.0001, for C3, C5, and sC5b-9, respectively). Composite scores and activity indices were also moderately correlated with proteinuria (uPCR; r = 0.44 and 0.43, p = 0.0211 and 0.0259, respectively). In contrast, chronicity indices were correlated with both eGFR and FD (r = −0.57 and 0.60, p = 0.0021 and 0.0009, respectively) and, although not significantly with plasma Ba, were significantly correlated with urinary Ba concentrations (r = 0.69, p < 0.0001) and to a lesser extent with disease duration (r = 0.46, p = 0.017) and proteinuria (uPCR, r = 0.51, p = 0.0072) (Fig. 3).

Discussion

AP dysregulation is a key driver of the development of C3G, but further insight is needed into the extent of AP dysregulation in fluid (circulation) and surface (glomerular microenvironment) compartments [3, 4]. This analysis utilized baseline data from patients with central pathologist-confirmed C3G to investigate characteristics of complement pathway activity in the fluid phase and in conjunction with kidney function and biopsy scores. The goals were to identify potential biomarkers of clinical importance, to further our understanding of C3G pathophysiology, and to better define the patient population.

The characteristics of the analysis population were consistent with previously reported patient characteristics of C3G. Patients were young, with histologic evidence of CKD, and had received supportive treatments (e.g., angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, or immunosuppressants) and in some cases eculizumab without success; additionally, some were positive for genetic variants and autoantibodies targeting the AP [2, 4, 7, 11, 12, 20-22]. Consistent with a chronic and progressive disease, characteristics including biopsy scores, eGFR, and concentrations of fluid phase complement biomarkers varied across this population.

Our findings confirm the systemic dysregulation of the alternative and terminal complement pathway as a hallmark of C3G in these patients. Serum and plasma complement biomarker concentrations were distributed across a wide spectrum but in a pattern indicating AP-selective activation; median concentrations of C3 and C5 were lower than the normal range, yet C4 was within normal range in most individuals, and median sC5b-9, Bb, and Ba approached or exceeded the ULNs [11, 12]. A subset of patients had normal levels of AP biomarkers; whether this represents localized solid phase complement dysregulation could not be assessed. Notably, low serum concentrations of C3 correlated strongly with low C5 and high sC5b-9. Interestingly, the exceptional patients who showed systemic C3 reduction without sC5b-9 elevation were more likely to have DDD rather than C3GN (not shown), although the sample size was small for formal analysis. This is consistent with current understanding that C3GN is characterized by greater terminal complement activation relative to DDD [12].

Whether initiated by activation in the fluid phase or more directly on glomerular surfaces, the deposition of complement fragments in the glomerulus and the accompanying production of C3a and C5a, causing leukocyte infiltration and cytokine-mediated glomerular injury, likely accounts for the kidney damage [3]. Notably, complement biomarkers were also observed in urine, and increasing urinary concentrations of sC5b-9 were correlated with increases in both plasma sC5b-9 and proteinuria. The association with total proteinuria may represent nonselective urinary loss of larger molecular weight complexes, although the further contribution of local glomerular activation cannot be excluded. Nevertheless, urine sC5b-9 is likely to provide a useful and noninvasive biomarker for disease monitoring.

Strong correlations were observed between elevated FD and Ba concentrations and reduced glomerular filtration, and although the role of renal metabolism on the dynamics of these low-molecular weight proteins has long been known [23-25], it merits continued attention, particularly when considering the use of Ba, for example, as a biomarker of AP activation in C3G and other diseases affecting the kidneys. Additionally, the likelihood of elevated FD levels in patients with kidney injury may need to be considered when optimizing dosing regimens for investigational FD inhibitors for patients with renal impairment.

Finally, our analysis revealed notable correlations between systemic biomarkers and glomerular histologic scores. The biopsy composite score and its component activity index showed moderate to strong correlations with the systemic complement biomarkers C3, C5, and sC5b-9, such that greater systemic AP dysregulation was associated with more active glomerulonephritis. The biopsy chronicity index in contrast was much less correlated with systemic complement biomarkers and instead showed greater correlation with eGFR, supporting the notion that histologic chronicity index serves as a correlate of disease progression. The correlations of both activity and chronicity scores with proteinuria highlight the respective contributions of active disease and progressive damage to renal dysfunction. Previous efforts at histologic scoring in patient cohorts have been reported [2, 26-28]. Among the findings of these studies, chronicity scores reportedly are more predictive of renal outcome, whereas disease activity markers are not prognostic. However, the demonstration in the present study that histologic activity index correlates with systemic complement status indicates a mechanistic connection between complement and glomerular disease activity, which merits further investigation as selective complement inhibitors are evaluated for clinical efficacy in halting or reversing disease progression.

This study has several limitations that should be considered when interpreting these findings. The patient population was based on clinical trial enrollment and, therefore, is a relatively small and selective group of patients, which precluded any multivariate adjustments. Given the small sample size, the low number of patients subclassified with DDD limited any meaningful analyses of these patients for biopsy or biomarker analysis. In addition, the composite scoring system used in our study has not previously been published or fully validated. However, a study of the predictive value of the histological features utilized in the scoring system has recently been published [29].

We present here an evaluation of a well-defined cohort of C3G patients, which includes examination of pairwise correlations among complement biomarkers, clinical parameters, and biopsy scores. Findings from this study highlight important correlations that may have a role in understanding the interplay between complement and clinical biomarkers in this population. Additional such studies in larger cohorts and in conjunction with clinical efficacy assessments are warranted to further strengthen the connections between complement activation and disease presentation and to validate specific therapeutic targets in the C3G population or subpopulations. Further research is needed to provide additional parameters to more precisely segment patients and to verify the potential responsiveness of each patient to complement inhibitory drugs such that they can be incorporated into the design of clinical trials for this rare disease.

Acknowledgments

The authors would like to thank the patients who have enrolled in the two clinical trials and their families. Our gratitude also goes to Dr. Tom Barbour (who passed away) for his substantial contributions to these studies. In addition, we are grateful to Guillermo del Angel and Nader Najafian of Alexion, AstraZeneca Rare Disease, for their assistance with clinical study monitoring, genetic analysis of patient samples, and review of the manuscript and to Dharaben Patel and Yongsen Zhao of Alexion, AstraZeneca Rare Disease, for their contributions of systemic and urinary complement biomarker data. The sponsor provided a formal review of the publication; however, the authors had final authority over the content. Medical writing support was provided by Helen Swainston, Bioscript Group, Macclesfield, UK, which was funded by Alexion, AstraZeneca Rare Disease.

Statement of Ethics

This clinical trial was evaluated and approved by the Institutional Review Board or Independent Ethics Committee at each participating center, and the study was conducted in accordance with the Declaration of Helsinki and the Council for International Organizations of Medical Sciences International Ethical Guidelines. A full list of Institutional Review Boards/Independent Ethics Committees can be found in the online Supplementary Information (S3). All participants provided written informed consent/assent prior to enrolling in the study.

Conflict of Interest Statement

Steven D. Podos, Kara Rice, Jane A Thanassi, and Mingjun Huang are employees of Alexion, AstraZeneca Rare Disease, and are shareholders in the company. Carla Nester is the Associate Director for Molecular Otolaryngology and Renal Research Laboratory and has received a grant/contract from NIH. She has been a site investigator for ChemoCentryx, Achillion Pharmaceuticals, Alexion Pharmaceuticals, Novartis, Apellis Pharmaceuticals, Retrophin/Travere Therapeutics, and BioCryst. In addition, she has received advisory board honorarium from BioCryst and has participated in drug safety monitoring board/advisory board for Alexion Pharmaceuticals, Novartis, and BioCryst. Disclosures including royalties/licenses are provided in www.uptodate.com. Gerald Appel has received a research grant from Alexion Pharmaceuticals/Achillion Pharmaceuticals, which was paid to his institution (Columbia University, College of Physicians and Surgeons), and consultancy fees from Alexion Pharmaceuticals. Andrew S. Bomback has received consultancy fees from Achillion Pharmaceuticals/Alexion Pharmaceuticals, Catalyst, ChemoCentryx, Novartis, and Visterra. Terence Cook has received consultancy fees from Alexion Pharmaceuticals and Novartis and a grant from Alexion Pharmaceuticals, which was provided to his institution. Bradley Dixon has received consultancy fees from Alexion Pharmaceuticals and Apellis Pharmaceuticals. Craig Langman has received study funding and support from Alexion Pharmaceuticals, which was provided to his institution. Liz Lightstone has been a consultant/advisor for Achillion, Alexion Pharmaceuticals, AstraZeneca, Aurinia, Bristol-Myers Squibb, GSK, Kezar Life Sciences, Novartis, and Pfizer. She has received honoraria/travel grants from Alexion Pharmaceuticals, Achillion Pharmaceuticals, GSK, and Novartis and has participated in drug safety monitoring/advisory boards for Novartis. She has received study funding/support from Alexion Pharmaceuticals, which were provided to her institution. LL has also participated as the deputy chair of the Western Europe Regional Board and on ISN ExComm, is a trustee for Kidney Research UK, and a council member for Women in Nephrology (all unpaid). Samir V. Parikh has received grants/funding from NIH-NIDDK, EMD Serono, and Aurinia Pharmaceuticals, which were paid to institution, and consultancy fees from Aurinia Pharmaceuticals, Alexion Pharmaceuticals, Bristol-Myers Squibb, Glaxo­SmithKline, and Kezar Life Sciences. Disclosures including royalties/licenses are provided in www.uptodate.com. Matthew C. Pickering has received consultancy fees from Alexion Pharmaceuticals, Achillion Pharmaceuticals, and Gyroscope Pharmaceuticals and study funding from Achillion Pharmaceuticals. C. John Sperati has received honoraria from Alexion Pharmaceuticals for serving on the DMC of the clinical trials and research grant/contract support from Achillion Pharmaceuticals, Alnylam Pharmaceuticals, and Novartis Pharmaceuticals (paid to institution). CJS has received consultancy fees from Alnylam Pharmaceuticals and Q32 Bio. Howard Trachtman has received consultancy fees from Travere Therapeutics, Akebia Therapeutics, Goldfinch Bio, Angion, and Natera and support for meeting attendance from Travere Therapeutics. He has participated in data safety monitoring or advisory boards for Otsuka and ChemoCentryx. Jack Wetzels has received consultancy fees from Novartis (paid to institution), Morphosys, and Travere. He has received study funding/support from Alexion Pharmaceuticals, which was provided to his institution, and grant support and honoraria from Alexion Pharmaceuticals. JW is a member of KDIGO guide working groups (unpaid). Giuseppe Remuzzi has received consultancy fees from Akebia Pharmaceuticals Inc., Alexion Pharmaceuticals Inc., AstraZeneca, BioCryst Pharmaceuticals, Janssen Research and Development LLC, Menarini Ricerche Spa, Otsuka, and Silence Therapeutics, which were all paid to his institution. He has also received honoraria and support for meeting attendance from Boehringer Ingelheim. Koenraad Peter Bouman, Erica Daina, and James Tumlin have no conflicts to declare. Achillion Pharmaceuticals Inc. was acquired by Alexion Pharmaceuticals. Alexion Pharmaceuticals is now Alexion, AstraZeneca Rare Disease.

Funding Sources

This analysis and publication were funded by Alexion, AstraZeneca Rare Disease (and formerly by Achillion Pharmaceuticals, Inc.), who provided overall study management, performed the statistical analyses, and verified data accuracy.

Author Contributions

Carla Nester, Gerald Appel, Andrew Bomback, Bradley Dixon, Jack Wetzels, and Guiseppe Remuzzi: design of study, patient recruitment, data acquisition, and interpretation of data. Koenraad Peter Bouman, Erica Daina, Craig Langman, Liz Lightstone, Samir Parikh, Matthew Pickering, C. John Sperati, Howard Trachtman, and James Tumlin: patient recruitment, data acquisition, and interpretation of data. Terence Cook: design of study and central pathology review and scoring of kidney biopsies. Steven Podos and Minjun Huang: development of analysis plan, data analysis, and interpretation of data. Jane Thanassi: assay development and analysis of patient samples. Kara Rice: development of statistical analysis plan and data analysis. All authors provided critical review of the content of the manuscript and approval for its submission.

Data Availability Statement

Alexion will consider requests for disclosure of clinical study participant-level data provided that participant privacy is assured through methods like data de-identification, pseudonymization, or anonymization (as required by applicable law) and if such disclosure was included in the relevant study informed consent form or similar documentation. Qualified academic investigators may request participant-level clinical data and supporting documents (statistical analysis plan and protocol) pertaining to Alexion-sponsored studies. Further details regarding data availability and instructions for requesting information are available in the Alexion Clinical Trials Disclosure and Transparency Policy at https://alexion.com/our-research/research-and-development (link to Data Request Form: https://alexion.com/contact-alexion/medical-information).

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